forrint/bge-m3-embeddings-q4_k_m-gguf overview

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    "pipeline_tag": "sentence-similarity",
    "tags": [
      "sentence-transformers",
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    "license": "mit",
    "base_model": "megavn/bge-m3-embeddings",
    "frontmatter": {
      "pipeline_tag": "sentence-similarity",
      "tags": [
        "sentence-transformers",
        "feature-extraction",
        "sentence-similarity",
        "llama-cpp",
        "gguf-my-repo"
      ],
      "license": "mit",
      "base_model": "megavn/bge-m3-embeddings"
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    "summary": "This model was converted to GGUF format from megavn/bge-m3-embeddings using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.",
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    "readme_markdown": "---\npipeline_tag: sentence-similarity\ntags:\n- sentence-transformers\n- feature-extraction\n- sentence-similarity\n- llama-cpp\n- gguf-my-repo\nlicense: mit\nbase_model: megavn/bge-m3-embeddings\n---\n\n# bortunac/bge-m3-embeddings-Q4_K_M-GGUF\nThis model was converted to GGUF format from [`megavn/bge-m3-embeddings`](https://huggingface.co/megavn/bge-m3-embeddings) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.\nRefer to the [original model card](https://huggingface.co/megavn/bge-m3-embeddings) for more details on the model.\n\n## Use with llama.cpp\nInstall llama.cpp through brew (works on Mac and Linux)\n\n```bash\nbrew install llama.cpp\n\n```\nInvoke the llama.cpp server or the CLI.\n\n### CLI:\n```bash\nllama-cli --hf-repo bortunac/bge-m3-embeddings-Q4_K_M-GGUF --hf-file bge-m3-embeddings-q4_k_m.gguf -p \"The meaning to life and the universe is\"\n```\n\n### Server:\n```bash\nllama-server --hf-repo bortunac/bge-m3-embeddings-Q4_K_M-GGUF --hf-file bge-m3-embeddings-q4_k_m.gguf -c 2048\n```\n\nNote: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.\n\nStep 1: Clone llama.cpp from GitHub.\n```\ngit clone https://github.com/ggerganov/llama.cpp\n```\n\nStep 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).\n```\ncd llama.cpp && LLAMA_CURL=1 make\n```\n\nStep 3: Run inference through the main binary.\n```\n./llama-cli --hf-repo bortunac/bge-m3-embeddings-Q4_K_M-GGUF --hf-file bge-m3-embeddings-q4_k_m.gguf -p \"The meaning to life and the universe is\"\n```\nor \n```\n./llama-server --hf-repo bortunac/bge-m3-embeddings-Q4_K_M-GGUF --hf-file bge-m3-embeddings-q4_k_m.gguf -c 2048\n```\n",
    "related_quantizations": []
  },
  "tags": [
    "sentence-transformers",
    "gguf",
    "feature-extraction",
    "sentence-similarity",
    "llama-cpp",
    "gguf-my-repo",
    "base_model:megavn/bge-m3-embeddings",
    "base_model:quantized:megavn/bge-m3-embeddings",
    "license:mit",
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    "region:us"
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  "last_modified": "2026-03-16T17:23:25.000Z",
  "created_at": "2026-03-16T17:23:24.000Z",
  "pipeline_tag": "sentence-similarity",
  "library_name": "sentence-transformers"
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  "id": "Forrint/bge-m3-embeddings-Q4_K_M-GGUF",
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  "sha": "6bc5c393b789a981a1ceb51da1317c77c1fad2c7",
  "createdAt": "2026-03-16T17:23:24.000Z",
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